Recommendation platform for structured queries

ABSTRACT

In one example, a processor receives a structured query, parses the structured query into components, and stores the structured query, the components, and at least one attribute regarding the structured query in a first query record of a query record storage platform, the at least one attribute comprising a user identification of a user generating the structured query. The processor may then receive a search associated with the query record storage platform, where the search includes at least one parameter, and where the at least one parameter specifies at least one of the structured query, at least one of the components, or at least one of the at least one attribute regarding the structured query, and return the first query record in response to the search.

The present disclosure relates generally to structured queries, and moreparticular to a recommendation platform for querying structured datasets that enables users, e.g., analysts, data scientists/engineers,etc., to discover previous queries, data sources, and other users.

BACKGROUND

Data analysts may spend time trying to familiarize themselves with datasources that are new to them. Many organizations are affected by thisproblem, especially large organizations with many different data setsand legacy systems. For example, data analysts, such as businessintelligence personnel, data engineers, and data scientists, may spend asubstantial amount of time in meetings, sending e-mails, and makingphone calls to colleagues trying to figure out how to operate on datasources that are new to them. Additionally, data administrators may notknow who to notify if a data source is down or if there is going to be achange in the schema of a particular data source. In particular, dataadministrators may change over time, and the user bases of various datasources may also change as personnel retire or move on to differentprojects, different roles, or different organizations.

SUMMARY

In one example, the present disclosure provides a device,computer-readable medium, and method for returning a query record inresponse to a search associated with a query record storage platform.For example, a method may include a processor receiving a structuredquery, parsing the structured query into components, and storing thestructured query, the components, and additional information regardingthe structured query in a first query record of a query record storageplatform, the additional information comprising a user identification ofa user generating the structured query. The processor may then receive asearch associated with the query record storage platform, where thesearch includes at least one parameter, and where the at least oneparameter specifies at least one of the structured query, at least oneof the components, or at least one aspect of the additional informationregarding the structured query, and return the first query record inresponse to the search.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure can be readily understood by considering thefollowing detailed description in conjunction with the accompanyingdrawings, in which:

FIG. 1 illustrates one example of a communications network related tothe present disclosure;

FIG. 2 illustrates an example user interface for searching for queryrecords, for presenting search results, and for presentingrecommendations, according to the present disclosure;

FIG. 3 illustrates an example flowchart of a method for returning aquery record in response to a search associated with a query recordstorage platform; and

FIG. 4 illustrates a high-level block diagram of a computing devicespecially programmed for use in performing the functions describedherein.

To facilitate understanding, identical reference numerals have beenused, where possible, to designate identical elements that are common tothe figures.

DETAILED DESCRIPTION

The present disclosure broadly discloses device, non-transitory (i.e.,tangible or physical) computer-readable storage media, and methods forreturning a query record in response to a search associated with a queryrecord storage platform. In one example, the present disclosure relatesto structured data in a database system that can be accessed throughstructured query languages. For instance, users of a database system,such as data analysts, business intelligence personnel, data engineers,data scientists, and the like may spend a substantial amount of time inmeetings, sending e-mails, and making phone calls to colleagues tryingto figure out how to operate on data sources that are new to them. Inaddition, a user may have a task that calls for access to certain data,but the user may not even know if such data exists in the databasesystem, and if so, where the data resides, how to access the data, andso forth.

In one example the present disclosure provides a recommendation platformthat provides recommendations to users of the database system, such asrecommended queries, recommended other users, recommended databases,recommended data tables, recommended fields, recommended date ranges,recommended time ranges, and so forth. For example, the presentdisclosure may store query records regarding structured queries that areentered by users with respect to the database system. To illustrate, aquery record for a query may store the query itself, components of thequery, such as databases, data tables, fields, date ranges, commands,and so forth that are specified in the query, and attributes of thequery, such as a user generating the query, a time the query is entered,an outcome of the query (e.g., successful or unsuccessful execution), asize of a result of the query, e.g., if the query is to return records,perform a join, etc., and so forth. Recommendations may then be derivedfrom the query records that are stored over time. For example, a usermay not know how or where to begin a task related to the databasesystem, but may have certain parameters which the user believes may berelevant to the task. Accordingly, in one example, the user may performa search for query records using parameters such as an identification ofanother user, a particular database, data table, or field, or a date, atime, or a range of dates/times. The search parameters may then besearched against the stored query records and any query records meetingthe search parameter(s) (or meeting the search parameter(s) and anyadditional criteria) may be returned. In addition, one or morerecommendations may also be provided to the user in response to thesearch.

In one example, a user performing a search may select one or more filtercriteria for presenting query records responsive to the search. Forinstance, the user may select to filter by user identification (“userID”), by field, by date range, and so forth. To illustrate, if a usersubmits a search with the parameter of “employees” (the name of a datatable), and if the user selected to filter by user ID, query recordspresented in response to the search may include query records forqueries that included the component “employees” and which were submittedby a user specified in the filter criteria. It should be noted that if adatabase, data table, or field is “popular,” there may be many queryrecords associated with the database, data table, or field. Thus, todifferentiate among query records associated with the database, datatable, or field, sort by criteria may determine how the query recordsthat satisfy the search parameter(s) may be presented. For example, if“sort by” criteria is “date” or “time,” the most recent 10 queryrecords, 20 query records, etc. that satisfy the search parameter(s) (orthat satisfy the search parameter(s) and any filter criteria) mayinitially be presented, while additional query records may be retrievedand presented if the user indicates a desire to access additional queryrecords that are responsive to the search. Thus, in accordance with thepresent disclosure, the ranking and presentation of query records inresponse to a search may vary depending upon the particular parameter(s)entered, the filter criteria, and so forth.

In one example, recommendations may include users, databases, datatables, fields, date ranges, time ranges, and so forth. For example, fora particular data table in a database of the database system, thepresent disclosure may determine from the query records: users whoperform the most queries with respect to the data table, the mostpopular fields within the data table in terms of numbers of queries,number of times accessed, number of times returned in results of aquery, number of “joins,” etc., other data tables that are associatedwith the data table, such as when there is a significant number of timesthat the data table is “joined” with the other data table, when asignificant number of users access the data table and the other datatable within a given time period, a field in another data table that isrelated to a field specified in a search, (e.g., due to previoussuccessful “joins” of the data tables over the two fields, and so forth.Accordingly, relevant recommendations may then be generated and providedto a user based upon one or more search parameters that are entered bythe user. For instance, if a search parameter includes the data table,the recommendations may include: top users with respect to the datatable, popular fields with respect to the data table, other data tablesassociated with the data table, and so forth. The user may then havefurther insight into possible databases, data tables or fields toexplore, other users to follow to learn ways to interact with the data,and so on. In one example, users may rate other users, the queries/queryrecords of other users, the recommendations provided in response toparticular search parameters. This user feedback may then be used toadjust rankings of users, queries/query records, databases, data tables,fields, etc. overall or with respect to the search parameters and/or thefilter criteria.

To further illustrate, a practical example of the present disclosure isnow described. Users A and B may work in a small group that is part of alarge organization with many datasets. They have been assigned the taskof determining which customers will subscribe to cable television. UsersA and B know how to analyze the demographics database of the company,but they do not know how they can get information with respect to whomhas bought cable, when, and where. They would like to merge two datasources together to create a predictive model that informs managementwho is more likely to subscribe to cable television, but the second datasource must still be located.

In the absence of the present disclosure, users A and B may proceed asfollows. Users A and B may talk with manager C, who mentions that thereis a dataset that already has information about who subscribed to whatcable service, when they subscribed to the service and where. However,manager C does not know how to access the data, and does not know inwhich database and/or in which data table the data resides. Therefore,manager C informs users A and B to talk to user D, who many years agoworked with the dataset. After many e-mails, users A and B obtain fromuser D the name of the database and table. Users A and B start exploringthe dataset after their access request has been approved. However, afteran initial inspection of a “cable TV” table, users A and B do not knowthe meaning of each field. There is a field “name id”, another onecalled “customer_id” and another one called “ban,” among 100 otherfields. Users A and B ask user D, but user D does not remember and doesnot know who else has worked with the dataset.

With significant guessing and verification via manual inspection, user Afinally identifies that the field named “ban,” matches exactly to afield in a “demographics” table that is called “cust_uniq_id.” User Athen proceeds to join the data so that user B can build a model. Forinstance, user A may enter the structured query: “SELECTdemo.cust_uniq_id, cable.ban FROM demographics demo; JOINcontent_provider cable; ON (cable.ban=demo.cust_uniq_id).” However,unbeknownst to users A and B, user E faced the same task two yearsearlier and already presented the results to a different group. Thus,users A and B spent a significant amount of time and effort to redo thesame work previously performed by user E.

In contrast, with the benefit of the present disclosure, users A and Bmay avoid some or all of the above steps. For example, if user D is ableto tell users A and B that the relevant data table is called“content_provider,” users A and B may enter a search via a userinterface of a recommendation platform of the present disclosure. Inresponse to the search, users A and B may be presented with a list ofvarious query records associated with the “content_provider” table.Users A and B may then notice upon reviewing the list of query recordsthat a user E performed a large number of queries regarding the“content_provider” table within the last month. Thus, users A and B mayaccess the content_provider table for further insight and/or may contactuser E who may be able to provide helpful guidance. Alternatively, or inaddition, users A and B may be provided with one or more recommendationsbased upon the search parameter(s). For instance, “user E” may bepresented as a recommended user, a “demographics” table may be presentedas a recommended table, and so forth. For instance, the “demographics”table may be recommended by virtue of the fact that users may perform alarge number of operations, such as “joins” with respect to the“content_provider” table and the “demographics” table. Users A and B maythen explore the results of various queries of “user E,” e.g., byentering “user E” as a parameter of a new search and filtering by “userID,” receiving query records in response to the search, and repeatingone or more of the queries associated with the query records.

Users A and B may further specify to sort by “table” for the search.Accordingly, query records of queries by “user E” that include the“content_provider” table as a component may be easily located (e.g.,since query records may be listed alphabetically by table, those thatrelate to “content_provider” may be grouped together in the list). Inaddition, users A and B may also infer further actions to take, such assubmitting a request to an administrator that a combined dataset bestored to alleviate repeated execution of the same or similar joinoperations. Thus, these and other aspects of the present disclosure arediscussed in greater detail below in connection with the examples ofFIGS. 1-4.

To aid in understanding the present disclosure, FIG. 1 illustrates anexample system 100 comprising a plurality of different networks forsupporting the returning of a query record in response to a searchassociated with a query record storage platform, and other functions.Telecommunication service provider network 150 may comprise a corenetwork with components for telephone services, Internet services,and/or television services (e.g., triple-play services, etc.) that areprovided to subscribers, and to peer networks. In one example,telecommunication service provider network 150 may combine core networkcomponents of a cellular network with components of a triple-playservice network. For example, telecommunication service provider network150 may functionally comprise a fixed mobile convergence (FMC) network,e.g., an IP Multimedia Subsystem (IMS) network. In addition,telecommunication service provider network 150 may functionally comprisea telephony network, e.g., an Internet Protocol/Multi-Protocol LabelSwitching (IP/MPLS) backbone network utilizing Session InitiationProtocol (SIP) for circuit-switched and Voice over Internet Protocol(VoIP) telephony services. Telecommunication service provider network150 may also further comprise a broadcast television network, e.g., atraditional cable provider network or an Internet Protocol Television(IPTV) network, as well as an Internet Service Provider (ISP) network.With respect to television service provider functions, telecommunicationservice provider network 150 may include one or more television serversfor the delivery of television content, e.g., a broadcast server, acable head-end, a video-on-demand (VoD) server, and so forth. Forexample, telecommunication service provider network 150 may comprise avideo super hub office, a video hub office and/or a serviceoffice/central office. For ease of illustration, various components oftelecommunication service provider network 150 are omitted from FIG. 1.

In one example, access networks 110 and 120 may each comprise a DigitalSubscriber Line (DSL) network, a broadband cable access network, a LocalArea Network (LAN), a cellular or wireless access network, and the like.For example, access networks 110 and 120 may transmit and receivecommunications between endpoint devices 111-113, 121-123, andtelecommunication service provider network 150 relating to voicetelephone calls, communications with web servers via the Internet 160and/or other networks 130, 140, and so forth. Access networks 110 and120 may also transmit and receive communications between endpointdevices 111-113, 121-123 and other networks and devices via Internet160.

For example, one or both of access networks 110 and 120 may comprise anISP network, such that 111-113 and/or 121-123 may communicate over theInternet 160, without involvement of telecommunication service providernetwork 150. Endpoint devices 111-113 and 121-123 may each comprise atelephone, e.g., for analog or digital telephony, a mobile device, acellular smart phone, a laptop, a tablet computer, a desktop computer, aplurality or cluster of such devices, and the like. In one example, theaccess networks 110 and 120 may be different types of access networks.In another example, the access networks 110 and 120 may be the same typeof access network. In one example, one or more of the access networks110 and 120 may be operated by the same or a different service providerfrom a service provider operating telecommunication service providernetwork 150.

In another example, each of access networks 110 and 120 may comprise acellular access network, implementing such technologies as: globalsystem for mobile communication (GSM), e.g., a base station subsystem(BSS), GSM enhanced data rates for global evolution (EDGE) radio accessnetwork (GERAN), or a UMTS terrestrial radio access network (UTRAN)network, among others, where telecommunication service provider network150 may provide mobile core network 130 functions, e.g., of a publicland mobile network (PLMN)-universal mobile telecommunications system(UMTS)/General Packet Radio Service (GPRS) core network, or the like. Instill another example, access networks 110 and 120 may each comprise ahome network, which may include a home gateway, which receives dataassociated with different types of media, e.g., television, phone, andInternet, and separates these communications for the appropriatedevices. For example, data communications, e.g., Internet Protocol (IP)based communications may be sent to and received from a router in one ofaccess networks 110 or 120, which receives data from and sends data tothe endpoint devices 111-113 and 121-123, respectively.

In this regard, it should be noted that in some examples, endpointdevices 111-113 and 121-123 may connect to access networks 110 and 120via one or more intermediate devices, such as a home gateway and router,e.g., where access networks 110 and 120 comprise cellular accessnetworks, ISPs and the like, while in another example, endpoint devices111-113 and 121-123 may connect directly to access networks 110 and 120,e.g., where access networks 110 and 120 may comprise local area networks(LANs) and/or home networks, and the like.

In one example, organization network 130 may comprise a local areanetwork (LAN), or a distributed network connected through permanentvirtual circuits (PVCs), virtual private networks (VPNs), and the likefor providing data and voice communications. In one example,organization network 130 links one or more endpoint devices 131-134 witheach other and with Internet 160, telecommunication service providernetwork 150, devices accessible via such other networks, such asendpoint devices 111-113 and 121-123, and so forth. In one example,endpoint devices 131-134, comprise devices of organizational users of astructured database system, such as business intelligence personnel,data engineers, and data scientists.

In one example, endpoint devices 131-134 may each comprise a personalcomputer, a desktop computer, a laptop, a tablet computer, a bank orcluster of such devices, a mobile device, a cellular smart phone, and soforth. In one example, any one or more of endpoint devices 131-134 maycomprise software programs, logic or instructions for performing orsupporting one or more aspects of returning a query record in responseto a search associated with a query record storage platform, inaccordance with the present disclosure. In one example, organizationnetwork 130 may also include an application server (AS) 135. In oneexample, AS 135 may comprise a computing system, such as computingsystem 400 depicted in FIG. 4, and may be configured to provide one ormore functions for returning a query record in response to a searchassociated with a query record storage platform, in accordance with thepresent disclosure. For example, AS 135 may be configured to perform oneor more steps, functions, or operations in connection with the examplemethod 300 described below. In addition, AS 135 may interact withserver(s) 136 and/or sever(s) 155 which may store database system(s)and/or a query record storage platform, as described in further detailbelow. In one example, organization network 130 may be associated withthe telecommunication service provider network 150. For example, theorganization may comprise the telecommunication service provider, wherethe organization network 130 comprises devices and components to supportnetwork administration, business intelligence, and other data analysisfunctions.

In one example, the system 100 may include one or more servers 136and/or one or more servers 155 in organization network 130 andtelecommunication service provider network 150 respectively. In oneexample, the servers 136 and/or 155 may each comprise a computingsystem, such as computing system 400 depicted in FIG. 4, and may beconfigured to host one or more centralized system components which maycomprise all or a portion of a database system and/or a query recordstorage platform of the present disclosure. For example, a firstcentralized system component may comprise a database of assignedtelephone numbers, a second centralized system component may comprise adatabase of basic customer account information for all or a portion ofthe customers/subscribers of the telecommunication service providernetwork 150, a third centralized system component may comprise acellular network service home location register (HLR), e.g., withcurrent serving base station information of various subscribers, and soforth. Other centralized system components may include a customerrelationship management (CRM) system, an inventory system (IS), an ordersystem, the enterprise reporting system (ERS), the account object (AO)database system, and so forth. In any of these examples, the data storedby various centralized system components may comprise structured datastored in one or more database systems. In other words, server(s) 136and/or server(s) 155 may comprise one or more database systems inaccordance with the present disclosure. Still another centralized systemcomponent may comprise a query record storage platform storing queryrecords associated with user queries entered with respect to othercentralized system components, e.g., database(s) and/or databasesystem(s).

It should be noted that in one example, a centralized system componentmay be hosted on a single server, while in another example, acentralized system component may be hosted on multiple servers, e.g., ina distributed manner. Thus, an access of a centralized system componentmay, in some cases, involve accessing several physical servers. In oneexample, at least a portion of the data stored in servers 136 may becopied or derived from data on servers 155 in telecommunication serviceprovider network 150. For instance, servers 155 may collect call detailrecords (CDRs) in real time, while servers 136 may store summary recordsderived from the CDRs that are stored in a format that is accessible viaa structured query language.

In one example, one or more users of endpoint devices 131-134 maytherefore access various centralized system components in connectionwith performing tasks regarding a database system, such as enteringqueries, searching for query records in a query record storage platform,receiving recommendations, and so forth. An example user interface thatmay be displayed via devices 131-134 is described in greater detailbelow in connection with FIG. 2. In one example, users may connect to AS135 via devices 131-134, and AS 135 may retrieve data from databasesstored in server(s) 136 and/or server(s) 155 in response to userqueries. In addition, AS 135 may generate query records, store the queryrecords in a query record storage platform hosted on server(s) 136and/or server(s) 155, and retrieve the query records from server(s) 136and/or server(s) 155 to provide as recommendations in response to otheruser's searches. In other words, AS 135 may function as a recommendationplatform in accordance with the present disclosure.

The foregoing describes just one example of a system or network in whichexamples of the present disclosure may be implemented. Thus, it shouldbe realized that the network 100 may be implemented in a different formthan that illustrated in FIG. 1, or may be expanded by includingadditional endpoint devices, access networks, network elements,application servers, etc. without altering the scope of the presentdisclosure. It should also, be noted that the example of FIG. 1 ispresented in connection with an organization that operates atelecommunication service provider network. However, other, further, anddifferent examples of the present disclosure may relate to a databasesystem of a different type of entity, such as a bank, a school, ahospital, an insurance company, and so forth. As such, it should beunderstood that various other types of network architectures may bedeployed in connection with examples of the present disclosure forreturning of a query record in response to a search associated with aquery record storage platform. As just one example, an insurance companymay store homeowner's insurance data and car insurance data in separatedatabases that reside within infrastructure of a cloud-based datastorage platform. In one example, a user may access these databases tocorrelate customers who have both homeowner's insurance and carinsurance with the company through a personal computer connected to thecloud-based data storage platform via a corporate local area network(LAN) and the Internet. The insurance company may further store queryrecords in a query record storage platform residing within the same ordifferent cloud-based infrastructure as the database system storing thehomeowner's insurance data and the car insurance data. Thus, these andother variations are all contemplated within the scope of the presentdisclosure.

To further aid in understanding the present disclosure, FIG. 2illustrates an example user interface 200 which may be presented on auser device for searching for query records, for presenting searchresults, and for presenting recommendations, in accordance with thepresent disclosure. User interface 200 includes a query window 210, asearch window 220, a search results window 230, and a recommendationwindow 240. With respect to query window 210, a user may enter queriesand receive the results of queries. For instance, a current query 211may be input but not yet entered. The current query 211 may comprise,for example: “SELECT name, income FROM employees WHERE income>10 ORDERBY name.” In this case, only “name” and “income” would be selected foreach record of the table “employees”. Results would be sortedalphabetically by “name” and only records where “income” is greater than10 would be fetched. In addition, a last/previous query 212 may alsoappear in the query window 210, e.g., depending upon the space or numberof lines available, the number of lines of the current query 211, etc.In one example, query results may be presented within query window 210,or may be accessed and/or presented via a separate window (not shown).

In one example, query records for queries entered via query window 210and though other user devices may be stored and made accessible to otherusers performing searches in accordance with the present disclosure. Inparticular, the query described above specifies table names, fieldnames, filtering conditions and ranking methods. Because of thestructured format, queries of this nature may provide information as tohow to join tables, which fields are unique, which databases arerelated, the type(s) of data contained in a particular field, whichfields have the same content but different labels, which users aresubject matter experts, which tables/databases are most important, andso on. However, if the queries are not stored and are not made availablefor further use, the knowledge represented by such queries may be lost.

In one example, search window 220 includes a search bar 221, a filtercriteria selection box 222 and a “sort by” box 223. In one example, auser may enter one or more search parameters in search bar 221, such asan identification of a user, a database, a data table, a field, adate/time range, and so forth. In one example, a user may select zero,or one or more filter criteria, such as result size, execution time,number of tables, etc., via filter criteria selection box 222. Inaddition, in one example, the user may select zero, or one or moresort-by criteria via “sort by” box 223. The filter criteria selected mayexclude or confine results to only those results that conform to thefilter criteria. In addition, the sort-by criteria may affect the orderin which the results of the search are presented in search resultswindow 230. For instance, the present disclosure may invoke a searchengine and/or include search engine functionality to perform a searchaccording to the search parameter(s), as well as the filter criteriaand/or “order by” criteria, and to return a set of relevant results 231in results window 230.

As illustrated in FIG. 2, the results 231 in search results window 230include two query records, or at least a portion thereof. For instance,as mentioned above, a query record may include a query, components ofthe query, and attributes regarding the query. In the present example,results 231 are presented in a table with columns for “user,” “table,”“query,” and “time.” The “user” and “time” fields may be considered“attributes” of the query. The “query” field is for the full query, andthe “table” field represents one of the “components” of the query, i.e.,any table(s) specified in the query. For instance, in the presentexample, a user may have entered “sales” in the search bar 221 and mayhave filtered by the date of Jan. 1, 2016 (“2016-01-01”). As such, theresults may include two query records, both of which relate to the table“sales,” and both of which are from the relevant date. In one example,the user may also have selected to sort by “time” via the “sort by” box223. As such, the query record for an earlier query may appear first inthe results 231, followed by the query record for a later query.Alternatively, the user may have selected to sort by “user” via the“sort by” box 223. As such, the query record associated with a query ofuser “IH197F” may appear first followed by the query record associatedwith the query of user “RP895A.” In other words, the query records mayhave presented in alphabetical order by user ID in the results 231.

In addition to returning results of a search, the present disclosure mayalso provide recommendations, e.g., based upon the last entered search.For example, as illustrated in FIG. 2, recommendation window 240 mayprovide recommendations, e.g., in one or more lists 241. For instance, arecommended subject, such as a recommended query, a recommended user, arecommended database, a recommended data table, a recommended field, arecommended date range, a recommended time range, or a recommended dataoperation may be determined based upon the search parameter(s), or basedupon the search parameter(s) along with the filter criteria and/or thesort-by criteria. In one example, the recommendations of the list(s) 241may therefore be associated with recommended subjects that may beidentified. For instance, the table “employees” may have been “joined”several times with the table “Sales.” Therefore, a search parameter of“sales” may return the results 231 in search results window 230, and mayalso lead to a recommended table of “employees.” In addition, a searchparameter of “sales” may lead to a recommended user “CM237H.” Forexample, user “CM237H” may generate a greater number of queriesregarding the “Sales” table than other users. As such, a query recordregarding the table “Sales” and a query generated by user “CM237H” maybe provided as a recommendation, e.g., as the second entry in list 241.A user may then identify a recommended subject of interest and may usethe recommended subject as a search parameter for a subsequent search,for example.

In still another example, query records, components of query records,and/or query attributes may be rated by users with respect toapplicability or usefulness regarding a particular search parameter. Forinstance, another user may have entered a search parameter of “Sales”and received the same recommendations as presented in recommendationwindow 240. The previous user may have then provided a 4-star rating torecommendation of the “employees” table and a 2-star rating to the user“CM237H” with respect to that search parameter. When another user entersthe same search parameter, the ratings of therecommendations/recommendation subjects may therefore be presentedalongside the recommendations in the list(s) 241. In should be notedthat the foregoing describes only a few examples of how recommendationsmay be selected and presented in accordance with the present disclosure.For instance, in another example, recommendations may be presented inthe form of query records. For example, after a recommended subject isidentified, one or more query records associated with the recommendedsubject may be selected and presented via the recommendation window 240.

In still other examples, ratings of possible recommended subjects may bedetermined with respect to various search parameters in different ways.For instance, if the at least one recommended subject comprises arecommended user, the rank may be based upon a number of queries of therecommended user with respect to a database, a data table, or a fieldspecified in the search. In another example, if the at least onerecommended subject comprises a recommended database, the rank may bebased upon at least one of: a volume of queries associated with therecommended database, or a volume of joining of data tables of therecommended database. In another example, if the at least onerecommended subject comprises a recommended data table, the rank may bebased upon at least one of: a volume of queries associated with therecommended data table, or a volume of joining of the recommended datatable. In still another example, if the at least one recommended subjectcomprises a recommended field, the rank may be based upon at least oneof: a volume of queries associated with the recommended field, or avolume of joining over the recommended field. Thus, these and othervariations are all contemplated within the scope of the presentdisclosure.

FIG. 3 illustrates an example flowchart of a method 300 for returning ofa query record in response to a search associated with a query recordstorage platform. In one example, the steps, operations, or functions ofthe method 300 may be performed by any one or more of the components ofthe system 100 depicted in FIG. 1. For instance, in one example, themethod 300 is performed by the application server 135. Alternatively, orin addition, one or more steps, operations or functions of the method300 may be implemented by a computing device having a processor, amemory and input/output devices as illustrated below in FIG. 4,specifically programmed to perform the steps, functions and/oroperations of the method. Although any one of the elements in system 100may be configured to perform various steps, operations or functions ofthe method 300, the method will now be described in terms of an examplewhere steps or operations of the method are performed by a processor,such as processor 402 in FIG. 4.

The method 300 begins at step 305 and proceeds to step 310. At step 310,the processor receives a structured query. The structured query may beentered by a user against a database system with one or more databases.Each database may have one or more data tables, and each data table mayhave one or more fields populated with data. The structured query may beentered in a structured query language, and the database system maystore data in a structured format that is accessible via structuredqueries.

At step 320, the processor parses the structured query into components.For example, components of the structured query may include types ofdata operations contained in the structured query such as JOIN, SELECT,ORDER BY, etc., databases, data tables, or fields that are identified inthe structured query, a date range or a time range specified in thequery, and so forth.

At step 330, the processor stores the structured query, the components,and at least one attribute regarding the query in a first query recordof a query record storage platform. In one example the query recordstorage platform may share hardware with the database system. In anotherexample, the query record storage platform and the database system mayutilize different infrastructure. In one example, the at least oneattribute includes a user identification of a user generating the query.In one example, the at least one attribute may further include a time ofthe query and/or a size of a result of the query.

At step 340, the processor receives a search associated with the queryrecord storage platform, the search including at least one parameter,the at least one parameter specifying at least one of: the query, atleast one of the components, or at least one of the at least oneattribute regarding the query. In one example, the search may alsoinclude or may be accompanied by one or more filter criteria and one ormore “sort by” criteria.

At step 350, the processor returns the first query record in response tothe search. For example, the first query record may be selected by theprocessor, responsive to the search, if the query record is in some wayassociated with the at least one parameter of the search. For instance,the first query record may include the component “employees” if thestructured query received at step 310 includes this term. Thus, if thesearch includes the parameter of “employees,” the first query record maybe returned in response to the search (e.g., since the first queryrecord includes the table “employees” as one of the components). In oneexample, the first query record is returned in response to the searchwhen the first query record is associated with the at least one searchparameter and when the first query record satisfies a filter criteriaand/or a “sort by” criteria that is included in, or which accompaniesthe search received at step 340. With respect to the “sort by” criteria,the processor may initially select, for example, a top 10 query records,a top 20 query records, etc. to return at step 350. For instance, if thefilter criteria is a particular date, and the “sort by” criteria is“time,” a first 20 query records in time order from the specified datemay be returned. In one example, the processor may offer to a user toview additional query records after initially presenting the first 20query records based upon the “sort by” criteria, e.g., a next 20 queryrecords in time order from the specified date, and so forth. Followingstep 350, the method 300 may proceed to step 395 or to any one ofoptional steps 360-390.

At optional step 360, the processor may generate at least onerecommendation based upon the search. In one example, the at least onerecommendation identifies at least one recommended subject. The at leastone recommended subject may comprise, for example: a recommended query,a recommended user, a recommended database, a recommended data table, arecommended field, a recommended date range, a recommended time range,or a recommended type of data operation (e.g., a command, operation, ora sequence of commands or operations of a structured query language). Inone example, the at least one recommended subject may be selected basedupon a rank of the at least one recommended subject with respect to theat least one search parameter.

At optional step 370, the processor may present the at least onerecommendation to a user generating the search. For instance, the atleast one recommendation may be presented on a user endpoint device viaa user interface, such as user interface 200 illustrated in FIG. 2. Inone example, the at least one recommendation may be presented bydisplaying the at least one recommended subject, e.g., without furtheraccompanying information. For instance, the at least one recommendationmay be presented within a list of one or more recommended subjects,e.g., in a format such as list 241 in FIG. 2. Alternatively, or inaddition, the at least one recommendation may be presented by displayingat least one query record that includes the at least one recommendedsubject.

At optional step 380, the processor may receive feedback regarding theat least one recommendation from a user generating the search. Forexample, the user may take various actions with respect to the at leastone recommendation, such as submitting additional searches with respectto the at least one recommended subject. For instance, if a recommendeduser is included in the recommendation presented at optional step 370,the user may then submit an additional search for query recordsassociated with queries submitted by the recommended user.Alternatively, or in addition, the user may contact the recommended userfor assistance. In any case, if the user finds the at least onerecommendation to be helpful to the user's task, the user may providepositive feedback, e.g., rating the at least one recommendation, the atleast recommended subject, and/or a query record presented at optionalstep 370 more positively on a scale of one to ten, zero to five stars,etc. On the other hand, if the user finds the at least onerecommendation to be unhelpful, or not relevant to the user's task, theuser may rate the at least one recommendation, the at least recommendedsubject, and/or a query record presented at optional step 370 morenegatively.

At optional step 390, the processor may adjust a rank of the at leastone recommended subject based upon the feedback. For instance, in oneexample, the rating received at optional step 380 and/or the ratings ofother users may be used in calculating a rank of the at least onerecommended subject with respect to the at least one parameter of thesearch. In other words, different ranks may be calculated for the atleast one recommended subject for different search parameters. In oneexample, user ratings of different recommended subjects may comprise oneof several factors that may be used in calculating the rank. Forinstance, the number of times in a given time period that a database,data table, or field is accessed may also affect the rank of thedatabase, data table, or field. For example, the more the database, datatable, or field is accessed, the higher the rank.

Following step 350 or any one of optional steps 360-390, the method 300may proceed to step 395 where the method ends. In addition, although notspecifically specified, one or more steps, functions or operations ofthe method 300 may include a storing, displaying and/or outputting stepas required for a particular application. In other words, any data,records, fields, and/or intermediate results discussed in the method 300can be stored, displayed and/or outputted either on the device executingthe method 300, or to another device, as required for a particularapplication.

Furthermore, steps, blocks, functions, or operations in FIG. 3 thatrecite a determining operation or involve a decision do not necessarilyrequire that both branches of the determining operation be practiced. Inother words, one of the branches of the determining operation can bedeemed as an optional step. In addition, one or more steps, blocks,functions, or operations of the above described method 300 may compriseoptional steps, or can be combined, separated, and/or performed in adifferent order from that described above, without departing from theexamples of the present disclosure.

As such, the present disclosure provides at least one advancement in thetechnical field of structured query language operations on structureddatasets stored in database systems. This advancement is in addition tothe traditional methods of managing and manipulating structured datasetsvia a structured query language. In particular, the present disclosureincludes devices, non-transitory computer-readable storage media, andmethods that: receive a structured query, parse the structured queryinto components, store the structured query, the components, and atleast one attribute regarding the query in a first query record of aquery record storage platform, where the at least one attributecomprises a user identification of a user generating the query, receivea search associated with the query record storage platform, the searchincluding at least one parameter, the at least one parameter specifyingat least one of the query, at least one of the components, or at leastone of the at least one attribute regarding the query, and return thefirst query record in response to the search, as well as perform otheroperations. The present disclosure also provides a transformation ofdata, e.g., a structured query is parsed into components that are storedin a new query record along with attributes of the query. In addition,parameters of searches that are entered cause the generating of newdata, e.g., a recommendation that may include at least one recommendedsubject. Finally, examples of the present disclosure improve thefunctioning of a computing device, e.g., a server. Namely, a server forstructured query language operations on structured datasets is improvedby the use of operations for returning a query record in response to asearch associated with a query record storage platform, as describedherein.

FIG. 4 depicts a high-level block diagram of a computing devicespecifically programmed to perform the functions described herein. Asdepicted in FIG. 4, the system 400 comprises one or more hardwareprocessor elements 402 (e.g., a central processing unit (CPU), amicroprocessor, or a multi-core processor), a memory 404 (e.g., randomaccess memory (RAM) and/or read only memory (ROM)), a module 405 forreturning a query record in response to a search associated with a queryrecord storage platform, and various input/output devices 406 (e.g.,storage devices, including but not limited to, a tape drive, a floppydrive, a hard disk drive or a compact disk drive, a receiver, atransmitter, a speaker, a display, a speech synthesizer, an output port,an input port and a user input device (such as a keyboard, a keypad, amouse, a microphone and the like)). Although only one processor elementis shown, it should be noted that the computing device may employ aplurality of processor elements. Furthermore, although only onecomputing device is shown in the figure, if the method 300 as discussedabove is implemented in a distributed or parallel manner for aparticular illustrative example, i.e., the steps of the above method300, or the entire method 300 is implemented across multiple or parallelcomputing device, then the computing device of this figure is intendedto represent each of those multiple computing devices.

Furthermore, one or more hardware processors can be utilized insupporting a virtualized or shared computing environment. Thevirtualized computing environment may support one or more virtualmachines representing computers, servers, or other computing devices. Insuch virtualized virtual machines, hardware components such as hardwareprocessors and computer-readable storage devices may be virtualized orlogically represented.

It should be noted that the present disclosure can be implemented insoftware and/or in a combination of software and hardware, e.g., usingapplication specific integrated circuits (ASIC), a programmable gatearray (PGA) including a Field PGA, or a state machine deployed on ahardware device, a computing device or any other hardware equivalents,e.g., computer readable instructions pertaining to the method discussedabove can be used to configure a hardware processor to perform thesteps, functions and/or operations of the above disclosed method 300. Inone embodiment, instructions and data for the present module or process405 for returning a query record in response to a search associated witha query record storage platform (e.g., a software program comprisingcomputer-executable instructions) can be loaded into memory 404 andexecuted by hardware processor element 402 to implement the steps,functions or operations as discussed above in connection with theillustrative method 300. Furthermore, when a hardware processor executesinstructions to perform “operations,” this could include the hardwareprocessor performing the operations directly and/or facilitating,directing, or cooperating with another hardware device or component(e.g., a co-processor and the like) to perform the operations.

The processor executing the computer readable or software instructionsrelating to the above described method can be perceived as a programmedprocessor or a specialized processor. As such, the present module 405for returning a query record in response to a search associated with aquery record storage platform (including associated data structures) ofthe present disclosure can be stored on a tangible or physical (broadlynon-transitory) computer-readable storage device or medium, e.g.,volatile memory, non-volatile memory, ROM memory, RAM memory, magneticor optical drive, device or diskette and the like. Furthermore, a“tangible” computer-readable storage device or medium comprises aphysical device, a hardware device, or a device that is discernible bythe touch. More specifically, the computer-readable storage device maycomprise any physical devices that provide the ability to storeinformation such as data and/or instructions to be accessed by aprocessor or a computing device such as a computer or an applicationserver.

While various embodiments have been described above, it should beunderstood that they have been presented by way of example only, and nota limitation. Thus, the breadth and scope of a preferred embodimentshould not be limited by any of the above-described exemplaryembodiments, but should be defined only in accordance with the followingclaims and their equivalents.

What is claimed is:
 1. A device comprising: a processor; and acomputer-readable storage medium storing instructions which, whenexecuted by the processor, cause the processor to perform operations,the operations comprising: receiving a structured query; parsing thestructured query into components; storing the structured query, thecomponents, and at least one attribute regarding the structured query ina first query record of a query record storage platform, the at leastone attribute including a user identification of a user generating thestructured query; receiving a search associated with the query recordstorage platform, the search including at least one parameter, the atleast one parameter specifying at least one of: the structured query, atleast one of the components, or at least one of the at least oneattribute regarding the structured query; returning the first queryrecord in response to the search; and generating at least onerecommendation based upon the search, wherein the at least onerecommendation identifies at least one recommended subject, wherein theat least one recommended subject includes a recommended user, whereinthe recommended user is selected for the at least one recommendationbased upon a rank of the recommended user with respect to the at leastone parameter of the search, wherein the rank of the recommended user isbased upon a number of queries of the recommended user with respect to adatabase, a data table, or a field associated with the search.
 2. Thedevice of claim 1, wherein the at least one attribute further comprisesat least one of: a time of the structured query; or a size of a resultof the structured query.
 3. The device of claim 2, wherein the at leastone of the at least one attribute includes: the user identification ofthe user generating the structured query; the time of the structuredquery; or the size of the result of the structured query.
 4. The deviceof claim 1, wherein the components include at least one of: a databasespecified in the structured query; a data table specified in thestructured query; a field specified in the structured query; a daterange specified in the structured query; a time range specified in thestructured query; or a type of data operation specified in thestructured query.
 5. The device of claim 1, wherein the operationsfurther comprise: presenting the at least one recommendation to a usergenerating the search.
 6. The device of claim 5, wherein the presentingthe at least one recommendation comprises presenting at least one queryrecord associated with the at least one recommended subject.
 7. Thedevice of claim 5, wherein the operations further comprise: receiving afeedback regarding the at least one recommendation from the usergenerating the search; and adjusting at least one rank of the at leastone recommended subject based upon the feedback.
 8. The device of claim1, wherein the at least one recommended subject further comprises arecommended database, wherein the recommended database is selected forthe at least one recommendation based upon a rank of the recommendeddatabase with respect to the at least one parameter of the search,wherein the rank of the recommended database is based upon at least oneof: a volume of queries associated with the recommended database; or avolume of joining of data tables of the recommended database.
 9. Thedevice of claim 1, wherein the at least one recommended subject furthercomprises a recommended data table, wherein the recommended data tableis selected for the at least one recommendation based upon a rank of therecommended data table with respect to the at least one parameter of thesearch, wherein the rank of the recommended data table is based upon atleast one of: a volume of queries associated with the recommended datatable; or a volume of joining of the recommended data table.
 10. Thedevice of claim 1, wherein the at least one recommended subject furthercomprises a recommended field, wherein the recommended field is selectedfor the at least one recommendation based upon a rank of the recommendedfield with respect to the at least one parameter of the search, whereinthe rank of the recommended field is based upon at least one of: avolume of queries associated with the recommended field; or a volume ofjoining over the recommended field.
 11. A non-transitorycomputer-readable storage medium storing instructions which, whenexecuted by a processor, cause the processor to perform operations, theoperations comprising: receiving a structured query; parsing thestructured query into components; storing the structured query, thecomponents, and at least one attribute regarding the structured query ina first query record of a query record storage platform, the at leastone attribute including a user identification of a user generating thestructured query; receiving a search associated with the query recordstorage platform, the search including at least one parameter, the atleast one parameter specifying at least one of: the structured query, atleast one of the components, or at least one of the at least oneattribute regarding the structured query; returning the first queryrecord in response to the search; and generating at least onerecommendation based upon the search, wherein the at least onerecommendation identifies at least one recommended subject, wherein theat least one recommended subject includes a recommended user, whereinthe recommended user is selected for the at least one recommendationbased upon a rank of the recommended user with respect to the at leastone parameter of the search, wherein the rank of the recommended user isbased upon a number of queries of the recommended user with respect to adatabase, a data table, or a field associated with the search.
 12. Thenon-transitory computer-readable storage medium of claim 11, wherein thecomponents include at least one of: a database specified in thestructured query; a data table specified in the structured query; afield specified in the structured query; a date range specified in thestructured query; a time range specified in the structured query; or atype of data operation specified in the structured query.
 13. Thenon-transitory computer-readable storage medium of claim 11, wherein theoperations further comprise: presenting the at least one recommendationto a user generating the search.
 14. The non-transitorycomputer-readable storage medium of claim 13, wherein the presenting theat least one recommendation comprises presenting at least one queryrecord associated with the at least one recommended subject.
 15. Amethod, comprising: receiving, by a processor, a structured query;parsing, by the processor, the structured query into components;storing, by the processor, the structured query, the components, and atleast one attribute regarding the structured query in a first queryrecord of a query record storage platform, the at least one attributecomprising a user identification of a user generating the structuredquery; receiving, by the processor, a search associated with the queryrecord storage platform, the search including at least one parameter,the at least one parameter specifying at least one of: the structuredquery, at least one of the components, or at least one of the at leastone attribute regarding the structured query; returning, by theprocessor, the first query record in response to the search; andgenerating, by the processor, at least one recommendation based upon thesearch, wherein the at least one recommendation identifies at least onerecommended subject, wherein the at least one recommended subjectincludes a recommended user, wherein the recommended user is selectedfor the at least one recommendation based upon a rank of the recommendeduser with respect to the at least one parameter of the search, whereinthe rank of the recommended user is based upon a number of queries ofthe recommended user with respect to a database, a data table, or afield associated with the search.
 16. The method of claim 15, whereinthe at least one attribute further comprises at least one of: a time ofthe structured query; or a size of a result of the structured query. 17.The method of claim 16, wherein the at least one of the at least oneattribute includes: the user identification of the user generating thestructured query; the time of the structured query; or the size of theresult of the structured query.
 18. The method of claim 15, wherein thecomponents include at least one of: a database specified in thestructured query; a data table specified in the structured query; afield specified in the structured query; a date range specified in thestructured query; a time range specified in the structured query; or atype of data operation specified in the structured query.
 19. The methodof claim 15, further comprising: presenting the at least onerecommendation to a user generating the search.
 20. The method of claim19, wherein the presenting the at least one recommendation comprisespresenting at least one query record associated with the at least onerecommended subject.